Many new data are emerging in recent years - real time data is collected through digital health technologies, including apps and wearables, monitoring data, social media data, public datasets, and patient organization data, in addition to primary and secondary datasets. Real life data are highly informative and can be used to address a range of challenges throughout the product life cycle. Data from social media can generate valuable insights as patients often gather in digital communities to get answers and share their experiences. Conversations on social networks merit special consideration as they can have real world influence over treatment management decisions. Social media data can reveal the motivations that impact patient healthcare decisions and behaviors through each stage of the care pathway. These data provide both the patient and caregiver perspectives at the same time. For this reason, conversations on social networks offer an opportunity to deepen our understanding on: - The fears and hopes associated with patient treatments - Daily needs and difficulties patients are facing in managing their disease - The impact of disease on patient health related quality of life - Identification in real life of the stages of the care pathway and patient perceptions - Reactions to health policies Watch this webinar for insights on how to collect, use, analyze, and interpret social media data in different contexts. Our experts share knowledge from over fifteen years of successfully developing and adapting algorithms to treat this kind of data.

1. Copyright 2022. All Rights Reserved. Contact Presenter for Permission
Social Media Data:
Opportunities and Insights
for Clinical Research
Elodie de Bock, PhD
Senior Principal
Patient Centred Outcomes
ICON plc
elodie.debock@iconplc.com
Valentin Barbier, MSc
Research Associate
Patient Centred Outcomes
ICON plc
valentin.barbier@iconplc.com
Adel Mebarki, MBA
General Manager & Co-Founder
Health Technology
Kap Code
adel.mebarki@kapcode.fr
Joelle Malaab, MSc, MPH
International Project Manager
Health Technology
Kap Code
joelle.malaab@kapcode.fr

2. Social media data:
Opportunities and insights
for clinical research

3. A bit of theory: Social media listening and natural language processing
Application in real world setting: Merck case study
Testimonies: Nearly 2,000 from 262 patients and 679 caregivers
Results: Tables and graphs
Some interesting findings: Testimonies provide real world data that can be used to improve
the care process and patient quality of life
Perspectives for industry: Strengths of collecting the voices of patients and caregivers
throughout the full product life cycle
3
Today’s webinar agenda
Q&A

4. 4
Thanks to…
– Paul Loussikian, Pierre Foulquié, Simon Renner and Stephane Schuck (Analyses)
– Alexia Marrel (Qualitative input)
– Murtuza Bharmal (Sponsor)

5. 5
From Social Network
Data to Patient Insights

6. 6
Real time data
Primary & Secondary
Databases
A new world disrupted by data
Data collected through digital health technologies,
including apps and wearables.
For example: Hospital Episode Statistics, Prescription
data, etc.
For example, Drug Safety Monitoring Data
Data representing patients and service users’ views and
experiences, captured online
Public Health and Social Care authorities’ datasets
Data collected by patient organization
New types of data, among many others
Surveillance
& Monitoring
Social Media
Patient
Organisation
Data
Public
Datasets

7. 7
Conversations on social networks provide
insights into:
– The fears and hopes associated with their treatments
– Their daily difficulties and needs in managing their
disease
– The impact of their disease on their health-related
quality of life
– The real-life stages of the care pathway and patient
perceptions
– Reactions to health policies
Social networks cannot be ignored!
They can influence treatment decisions and change management. Patients gather in digital communities to get answers and share
their experiences
Social network data: A powerful tool to understand
patient perspective

8. 8
PRODUCT LIFECYCLE
LIFECYCLE
NO PHASE
RESEARCH
PRECLINICAL
& PHASE I
PHASE II PHASE III REGISTRATION PERI-POST
APPROVAL
Existing treatments’ experience perception: fears, hopes, challenges and unmet needs
Disease experience perception: daily difficulties and needs in disease management
Treatment experience
Gather patient insights throughout the full product life cycle
Patient insights, useful at each stage

9. 9
Illustrations - Tools
Developed by Kap Code

10. 10
Kap Code is a startup, spin off from the CRO Kappa Santé, dedicated to the analysis of real-life data and
more specifically data from social networks using artificial intelligence and NLP methods that translate
patient language into medical ontologies
DEDICATED TO THE
HEALTH SECTOR
SCIENTIFIC
EXPERTISE FOR OVER
15 YEARS
MULTIDISCIPLINARY TEAM
WITH MEDICAL
EXPERTISE
60 SCIENTIFIC WORKS
PUBLISHED
10
Kap Code in a few words

11. 11
Algorithms developed internally
Discussion topics
Specialty
Age, Sex
Difficulties encountered
Unmet needs
Creation of personas
Geolocation
Discussion topics
Care pathway
Quality of life
Difficulties encountered
Unmet needs
Creation of personas
Age, Sex
Geolocation
Perception
Care pathway
Quality of life
Difficulties encountered
Diagnostic error
Unmet needs
Vaccine perception
Disinformation
Identification of suicidal thoughts
Treatment intake
Therapeutic switch
Misuse
Signal detection
Discussion topics
Quality of life
Difficulties encountered
Unmet needs
Creation of personas
Age, Sex
Geolocation
Addressable digital populations
Patient
HCPs
Caregivers
Pathologies
Other
Treatment

12. 12
How does it work?
SOURCES
Generic and
specialized
Extraction Dataset
Pre-processing
Association rules
Topic models
Clustering
Topics of
discussions
Web users
typologies
Quality of Life
impacts
TERMINOLOGY
Lexical fields
(ex: healthcare pathway)
Encountered
difficulties
MODELING
ANALYSIS
Medical Vocabulary
(MedDRA)
Social networks and open
access forums, in
compliance with the GDPR
Patient journey

13. Detec’t – best in class AI for healthcare
13
I. II. III.
Important populations Quick & Accurate
Financial
Optimization
OBSERVE
à Infodemiology studies to
understand patients’ behaviour
à Health Related Quality of Life data
extraction
à Medical unmet needs and pain
points identification
à Care pathway analysis
à Patient & Caregivers recruitment
via Social networks
à Applied to Observational studies,
Focus groups and Clinical trials
ENGAGE
à Pharmacovigilance early signal
detection
à Fake news early detection
à Competition monitoring
MONITOR & ALERT

14. 14
14
Detec’t is an
automated social
network analysis
based on methods of
artificial intelligence
and text mining
Detec’t methodology
Yesterday I had an appointment at the hospital
with my OBGYN et and it seems that my
pregnancy get complicated, due to my
medications ... #FML
Yesterday I had an appointment at the
hospital with my OBGYN et and it seems that
my pregnancy get complicated, due to my
medications ... #FML
Pronoun
Verb
Event
Medical centre Healthcare
practicioner
Pregnancy
Therapeutics
Problematic
«Yesterday I had an appointment at the
hospital with my OBGYN et and it
seems that my pregnancy get
complicated, due to my medications ...
#FML »
1st category 2nd category 3rd category
EXTRACTION
ENTITY
DETECTION
STEMMING
MESSAGE
CLASSIFICATION

15. 15
Application in
Real World Setting

16. 16
Locally Advanced or
Metastatic Bladder
Cancer Online Study in
the United States

17. 17
Study objectives
Main topics of discussion Challenges and Unmet Needs
Treatment experience
perception
Phase 1 Phase 2 Phase 3
A social media study was conducted to improve Merck's knowledge of patients with locally advanced or metastasized
bladder cancer and their caregivers based in the United States1,2
These social media data were collected in 3 phases as shown below:
The study is based on the total volume of testimonies retrieved with their evolution over time. It also includes the typology
of online users (age and gender when available), as well as the distinction between patients and caregivers. The final
results presented are accompanied by examples of anonymized testimonies to support the findings
1 Renner S. et al. Perceived Unmet Needs in Patients Living With Advanced Bladder Cancer and Their Caregivers: Infodemiology Study Using Data From Social Media in the United States, JMIR Cancer 2022; 8(3)
2 Bharmal M. et al. Patient and Caregiver Perception of Treatments for Locally Advanced or Metastatic Bladder Cancer: Insights from Social Media in the US, ISPOR 2022, Washington, DC, USA

18. 18
WEB
Focus on testimonies discussing
advanced urothelial/bladder cancer
Extraction
Methodology
A 3-step extraction and filtration strategy was used to obtain a corpus of reliable caregiver and patient testimonies.
A qualitative analysis was then carried out to deepen and collect information on the challenges and unmet needs experienced by
these caregivers and these patients
144 029
testimonies
68 079
users
Removal of
nonmedical sources
1
Identification of patients’ &
caregivers’ experiences
2
3
Caregiver CORPUS
1,214
testimonies
679 caregivers
Quick Reminder
Qualitative analysis focusing on the
challenges and unmet needs mentioned in
caregiver testimonies
(saturation has been checked)
Patient CORPUS
688
testimonies
262 patients
“My husband had stage 4 bladder cancer
treated with removal of bladder and prostate
and construction of neobladder.”
User: person who mentioned bladder cancer online
Patient: person presenting as a bladder cancer patient
Caregiver: patient's relative involved or not in the care

19. 19
General descriptive data
Evolution of testimonies with a patient or a caregiver experience
regarding advanced BC over time
0
10
20
30
40
50
60
2
0
1
5
-
0
1
2
0
1
5
-
0
3
2
0
1
5
-
0
5
2
0
1
5
-
0
7
2
0
1
5
-
0
9
2
0
1
5
-
1
1
2
0
1
6
-
0
1
2
0
1
6
-
0
3
2
0
1
6
-
0
5
2
0
1
6
-
0
7
2
0
1
6
-
0
9
2
0
1
6
-
1
1
2
0
1
7
-
0
1
2
0
1
7
-
0
3
2
0
1
7
-
0
5
2
0
1
7
-
0
7
2
0
1
7
-
0
9
2
0
1
7
-
1
1
2
0
1
8
-
0
1
2
0
1
8
-
0
3
2
0
1
8
-
0
5
2
0
1
8
-
0
7
2
0
1
8
-
0
9
2
0
1
8
-
1
1
2
0
1
9
-
0
1
2
0
1
9
-
0
3
2
0
1
9
-
0
5
2
0
1
9
-
0
7
2
0
1
9
-
0
9
2
0
1
9
-
1
1
2
0
2
0
-
0
1
2
0
2
0
-
0
3
2
0
2
0
-
0
5
2
0
2
0
-
0
7
2
0
2
0
-
0
9
2
0
2
0
-
1
1
2
0
2
1
-
0
1
2
0
2
1
-
0
3
Number
of
testimonies
per
month
From January 1, 2015
to March 4, 2021
1,902 testimonies
941 patients or caregivers
28% patients (N=262/941)
72% caregivers (N=679/941)
88 sources

20. 20
Phase 1:
Main Topics of
Discussion

21. 21
The main topics of discussion in patient testimonies
Discussions around the diagnosis and
the different treatment possibilities
(traditional or alternative)
35.9 %
Exchange of messages of hope/support
and sharing of patient experiences
16.5 %
Discussions around the healthcare pathway
(patient management, method used for
screening/diagnosis, healthcare team, etc.)
15.2 %
Symptoms and clinical
signs of bladder cancer
8.5 %
Focus on patient quality of life
5.0 %
Others
19.0 %
5
themes
Ø Topics of discussion were identified using the Biterm Topic Modelling, an unsupervised machine learning method that identifies main topics in a
data set and categorizes messages according to these topics
Ø A manual interpretation of the topics then follows

22. 22
Sharing experiences and messages of
hope and support
22.5 %
Complications around bladder cancer
19.1 %
Focus on diagnosis methods and
medical acts
18.3 %
Scientific information on drug
treatments (clinical trials,
scientific articles, etc.)
9.3 %
Discussions around social coverage,
insurance and the financial
aspect around the care
5.3 %
Accompanying the patient in the
terminal phase and until death
7.6 %
Others
17.9 %
6
themes
The main topics of discussion in caregiver testimonies

23. 23
Phase 2: Challenges
and Unmet Needs

24. Patient Focus

25. 25
Main challenges and unmet needs during the journey*
B E F O R E B L A D D E R C A N C E R A F T E R
T R E A T M E N T / M E D I C A L I N T E R V E N T I O N S – 5 7 . 9 % (n=55)
• 29.5% Fear, occurrence, and management of treatment-related AEs and special
situations
• 7.4% General knowledge/information about a treatment
• 5.3% Difficulty or delay in accessing treatment
D I A G N O S I S &
S C R E E N I N G – 1 7 . 9 %
(number of challenges identified in patients’
testimonials =17)
• 9.5% Misdiagnosis/Prognosis
Error
• 6.3% Screening/Diagnostic delay
or lateness
P A T H O L O G Y – 2 6 . 3 % (n=25)
• 13.7% Progression/ Worsening/ Complication/ Recurrence of Disease
• 9.5% Consideration and management of symptoms of BC
• 2.1% Consideration and management of pain
H A R D S H I P S E X I S T I N G A T A L L S T E P S O F T H E J O U R N E Y / T R A N S V E R S A L – 4 2 . 1 % ( n = 4 0 )
21.1% Psychological impact: loneliness, depression, anxiety, fear, distress, personality change...
8.4% Need for sharing / Experiences / Support: discussion groups, social networks
4.2% Financial impact of the care: insurance, social coverage, cost...
C A R E & F O L L O W - U P – 1 4 . 7 % (n=14)
• 3.2% Burden of care: frequency of hospitalizations, numerous consultations,
emergency room visits, etc.
• 3.2% Disagreement in care: heterogeneity of medical decisions and opinions,
disagreement between patient and medical team
• 3.2% Problems of training or practice of the care team: lack of practice, lack of
knowledge of the pathology
R E M I S S I O N – 8 . 4 % (n=8)
• 7.4% Sequelae of illness or care
I M P A C T O N P A T I E N T E N V I R O N M E N T – 6 . 3 %
• 2.1% Professional impact for the patient: part-time therapy, work interruptions,
etc.
• 2.1% Change in relationship: couple, family, friends
• 2.1% Impact on daily activities
(n=6)
*340 testimonies analyzed of which 95 included challenges or unmet needs

26. 26
21.1%
n=20
13.7%
n=13
9.5%
n=9
9.5%
n=9
8.4%
n=8
7.4%
n=7
7.4%
n=7
6.3%
n=6
5.3%
n=5
29.5%
n=28
1
Fear, occurrence, and management of treatment-related
AEs and special situations
2
Psychological impact
Loneliness, depression, anxiety, fear, distress, personality
change...
3
Progression/Worsening
Complication/Recurrence of Disease
4 Misdiagnosis/Prognosis Error
5 Consideration and management of symptoms of BC
6
Need of Sharing /
Experiences / Support
discussion groups, social networks
7 General knowledge/information about a treatment
8 Sequelae of illness or care
9
Screening/Diagnostic
delay or lateness
10 Difficulty or delay in accessing treatment
Main unmet needs and challenges mentioned in
patients’ testimonies*
*340 testimonies analyzed of which 95 included challenges or unmet needs
TOP
10

27. Caregiver Focus

28. 28
Main challenges and unmet needs during the journey*
B E F O R E B L A D D E R C A N C E R A F T E R
T R E A T M E N T / M E D I C A L I N T E R V E N T I O N S – 3 5 . 0 % (n=62)
• 12.4% Fear, occurrence, and management of treatment-related AEs and special
situations
• 6.2% Wandering, therapeutic dead ends or ineffective treatments
• 5.6% Difficulty or delay in accessing treatment
D I A G N O S I S &
S C R E E N I N G – 1 5 . 3 %
(number of challenges identified in caregivers’
testimonials =27)
• 7.3% Screening/Diagnostic delay
or lateness
• 4.0% Fear/Shock of the diagnosis
disclosure
• 3.4% Misdiagnosis/Prognosis
Error
P A T H O L O G Y – 2 3 . 2 % (n=41)
• 6.2% Consideration and management of symptoms of BC
• 5.1% Progression/ Worsening/ Complication/ Recurrence of Disease
• 3.4% Altered general condition: fatigue, weight loss
H A R D S H I P S E X I S T I N G A T A L L S T E P S O F T H E J O U R N E Y / T R A N S V E R S A L – 5 0 . 8 % ( n = 9 0 )
26.0% Psychological impact: loneliness, depression, anxiety, fear, distress, personality change...
15.8% Need for sharing / Experiences / Support: discussion groups, social networks
4.5% Financial impact of the care: insurance, social coverage, cost...
C A R E & F O L L O W - U P – 1 2 . 4 % (n=22)
• 3.4% Communication problems: lack of empathy, lack of information transmission
• 2.3% Disagreement in care: heterogeneity of medical decisions and opinions,
disagreement between patient and medical team
• 2.3% Difficulty in accessing care: distance from the place of care, medical desert,
difficulty in making an appointment, insufficient number of HCPs, lack of availability of
HCPs or specialists
R E M I S S I O N – 4 . 0 % (n=7)
• 3.4% Sequelae of illness or care
E N D O F L I F E & D E A T H –
1 2 . 4 % (n=22)
• 10.2% Burden of end-of-life support for the
patient or loved ones & grief work
• 2.3% End-of-life management and
palliative care
I M P A C T O N P A T I E N T E N V I R O N M E N T – 1 7 . 0 %
• 9.6% Impact of being a caregiver: energy-consuming support for caregivers,
time-consuming, moving...
• 5.1% Change in relationship: couple, family, friends
• 1.1% Impact on daily activities
(n=30)
*423 testimonies analyzed of which 177 included challenges or unmet needs

29. 29
15.8%
n=28
12.4%
n=22
10.2%
n=18
9.6%
n=17
7.3%
n=13
6.2%
n=11
6.2%
n=11
5.6%
n=10
5.1%
n=9
26.0%
n=46
1
Psychological impact
Loneliness, depression, anxiety, fear, distress, personality
change...
2
Need of Sharing /
Experiences / Support
discussion groups, social networks
3
Fear, occurrence, and management of treatment-related
AEs and special situations
4
Burden of end-of-life support for the patient or loved ones
& grief work
5
Impact of being a caregiver
energy-consuming support for caregivers, time-consuming,
moving...
6
Screening/Diagnostic
delay or lateness
7
Wandering, therapeutic dead ends or ineffective
treatments
8
Consideration and management of symptoms
characteristic of BC
9 Difficulty or delay in accessing treatment
10
Change in relationship
couple, family, friends
Caregiver Patient Both
Main unmet needs and challenges mentioned in caregivers’ testimonies
whether they are patient-centered, caregiver-centered or both*
*423 testimonies analyzed of which 177 included challenges or unmet needs
TOP
10

30. 30
Caregiver Patient Both
n=18
n=17
15.8%
n=28
n=7
n=5
n=9
n=3
n=4
1.7%
n=3
26.0%
n=46
1
Psychological impact
Loneliness, depression, anxiety, fear,
distress, personality change...
2
Burden of end-of-life support for the
patient & grief work
3
Impact of being a caregiver
energy-consuming support for
caregivers, time-consuming, moving...
4
Need of Sharing / Experiences /
Support
discussion groups, social networks
5
Fear/Shock of the diagnosis
disclosure
6 Acceptance of the disease
7
Change in relationship
couple, family, friends
8
General knowledge/scientific
information about BC
9
End-of-life management and
palliative care
10 Covid19
n=13
n=11
n=11
n=10
n=6
n=6
n=9
n=6
n=8
n=22
1
Fear, occurrence, and
management of treatment-related
AEs and specials situations
2
Screening/Diagnostic
delay or lateness
3
Wandering, therapeutic dead ends
or ineffective treatments
4
Consideration and management of
symptoms characteristic of BC
5
Difficulty or delay in accessing
treatment
6
Altered general condition
fatigue, weight loss
7 Misdiagnosis/Prognosis Error
8
Progression/Worsening/
Complication/ Recurrence of
Disease
9 Sequelae of illness or care
10
Financial impact of the care:
insurance, social coverage, cost...
RANK BASED ON CAREGIVER-CENTERED CHALLENGES RANK BASED ON PATIENT-CENTERED CHALLENGES
2.8%
6.2%
6.2%
10.2%
9.6%
4.0%
5.1%
3.4%
5.1%
5.6%
3.4%
3.4%
7.3%
12.4%
4.5%
1.7%
2.3%
Main unmet needs and challenges mentioned in caregivers’ testimonies
whether they are patient-centered, caregiver-centered or both*
*423 testimonies analyzed of which 177 included challenges or unmet needs

31. 31
Phase 3: Treatment
Experience Perception

32. 32
General data and overview of the collected perceptions
of treatment
A qualitative analysis was carried out specifically among the testimonies of patients and caregivers on relevant experiences concerning
treatments (n=299), whether chemotherapy OR immunotherapy
è Filtering of testimonies using key words related to the treatment area concerned
Overall treatment intake
80%
20%
All testimonies
(n=299)
Treatment was
not taken
Treatment was
taken
Patient testimonies
Overall perception of treatment
88% 12%
Caregiver testimonies
Treatment was
taken
Treatment was
not taken
Patient
testimonies
Caregiver
testimonies
All
testimonies
(n=122)
(n=177)
(n=299) (n=177) (n=122)
Treatment was
taken
Treatment was
not taken
45%
33%
5%
17%
No perception
expressed
Negative
Mixed
Positive
37%
43%
7%
13%
No perception
expressed
Negative
Mixed
Positive
57%
18%
2%
23%
No perception
expressed
Negative
Mixed
Positive
CHEMOTHERAPY : 222 testimonies (80 from patients / 142 from caregivers)
IMMUNOTHERAPY : 77 testimonies (42 from patients / 35 from caregivers)
75% 25%

33. Chemotherapy Focus

34. 34
52% 36% 5% 7%
71% 23% 6%
Overall data on perceptions of chemotherapy
Overall perception of treatment
Caregiver
posts
Patient
posts
All
testimonies
(n=222)
(n= 80)
(n= 142)
INSIGHTS
“Hello. I’ve been recently been dx’d with muscle invasive bladder
cancer which involves the urethra and a lymph node. Was
scheduled for surgery on August 18 first, but then canceled so
that I get chemo treatments first. Had the first one last
week and going for the 2nd one this week.”
Patient
“I knew what to expect and how miserable chemo was gonna be... I
suggest doing research to prepare yourself. […] It will be okay chemo is
so bad, minus the sickness and all. Family will get you threw this too! I
believe mine just came back after 3 years and am pretty nervous for my
sons sake. Its never fun hearing the doctor say "time for another round“.”
Overall treatment intake
84%
16%
All posts
(n=222)
Treatment was
not taken by
patients
Treatment was
taken by
patients
Patient posts
87% 13%
Caregiver posts
Treatment was
taken
Treatment was
not taken
(n=80)
(n=142)
Treatment was
taken by patients
Treatment was not
taken by patients
No perception expressed
Negative
Mixed Positive
No perception expressed
Negative
Positive
Negative
No perception expressed Mixed Positive
q Chemotherapy treatments are perceived more negatively (36%) than positively
(7%) overall, both in patient and caregiver testimonies
q Main perceived benefits of chemotherapy: effectiveness, extension of life span, and few
adverse events
q Main perceived drawbacks of chemotherapy: adverse events/pain, lack of effectiveness,
and access criteria
Caregiver
CHEMOTHERAPY : 222 testimonies (80 from patients / 142 from caregivers)
73% 27%
41% 44% 8% 7%

35. Immunotherapy focus

36. 36
26% 22% 5% 47%
29% 9% 7% 55%
Overall data on perceptions of immunotherapy
Overall perception of treatment
Caregiver
testimonies
Patient
testimonies
All
testimonies
(n=77)
(n= 42)
(n= 35)
INSIGHTS
“If so I just want you to know that Opdivo an
immunotherapy drug caused my metastatic lymph nodes to
disappear in 2 weeks. […] and the life saving Opdivo is
keeping the cancer that would kill me sooner at bay.”
Patient
“My husband was diagnosed with stage 4 bladder cancer (both small
cell and transitional cell carcenoma). He is currently taking
immunotherapy which has kept the other cancer at microscopic size
which has had numerous side effects like loss of taste buds
and loss of the adrenal and pituitary glands.”
Overall treatment intake
78%
22%
All testimonies
(n=77)
Treatment was
not taken
Treatment was
taken
Patient testimonies
88% 12%
Caregiver testimonies
Treatment was
taken
Treatment was
not taken
(n=42)
(n=35)
80% 20%
Treatment was
taken
Treatment was
not taken
No perception expressed
Negative
Mixed Positive
No perception expressed
Negative
Positive
Negative
No perception expressed Mixed Positive
Mixed
q Immunology treatments are perceived positively in almost half of the testimonies (47%)
q The perception of immunology treatments is more negative in caregivers' testimonies (37%)
than in patients' testimonies (10%)
q Main perceived benefits of immunotherapy: effectiveness, few adverse events, targeted therapy
q Main perceived drawbacks of immunotherapy: lack of effectiveness, AE/pain, and long-term
sequelae
Caregiver
IMMUNOTHERAPY : 77 testimonies (42 from patients / 35 from caregivers)
23% 37% 3% 37%

37. 37
Conclusion and
Key Insights

38. 38
Take away messages
Numerous patients and their caregivers share their voices about bladder cancer and its advanced forms on
social media in the USA. They share their concerns, challenges but also their perception of treatments. These
testimonies provide real-world data that can be used to improve the care process and quality of life
Importance of the
psychological aspect,
even for caregivers
Importance of information
about adverse events and
their management
Importance of support
services for patients and
their caregivers

39. 39
Summary of Key
Findings & Perspective

40. 40
– Social network data: real-world data that provide very rich panel information to
analyse patient and caregiver perspectives about disease and treatment
– This informs, clarifies and highlights the unmet needs in disease management
and in existing treatments
– Gather patient insights throughout the full product life cycle using social
network data can be a powerful strategy
– This can be used to:
– Improve the care process and the quality of life of patients
– Enhance adherence to treatment
– Tweak the perception of a specific treatment
– Etc.
To remember

41. 41
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